[pub] SEED: efficient clustering of next-generation sequences.

SEED: efficient clustering of next-generation sequences.

Source

Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.

Abstract

MOTIVATION:

Similarity clustering of next-generation sequences (NGS) is an important computational problem to study the population sizes of DNA/RNA molecules and to reduce the redundancies in NGS data. Currently, most sequence clustering algorithms are limited by their speed and scalability, and thus cannot handle data with tens of millions of reads.